Secure control protocol for universal serial bus mass storage devices

2015 ◽  
Vol 9 (6) ◽  
pp. 321-327 ◽  
Author(s):  
Jianghong Wei ◽  
Wenfen Liu ◽  
Xuexian Hu
Keyword(s):  
Mass Storage ◽  
Universal Serial Bus ◽  
Storage Devices ◽  
Control Protocol ◽  
Secure Control

scholarly journals A secure control protocol for USB mass storage devices

2010 ◽  
Vol 56 (4) ◽  
pp. 2239-2343 ◽  
Author(s):  
Fuw-Yi Yang ◽  
Tzung-Da Wu ◽  
Su-Hui Chiu
Keyword(s):  
Mass Storage ◽  
Storage Devices ◽  
Control Protocol ◽  
Secure Control

Frequent Itemset Mining and Association Rules

2010 ◽  
pp. 343-353
Author(s):  
Susan Imberman ◽  
Abdullah Uz Uz Tansel
Keyword(s):  
Credit Card ◽  
Scientific Data ◽  
Large Datasets ◽  
Medical Data ◽  
Frequent Itemset ◽  
Knowledge Discovery In Databases ◽  
Mass Storage ◽  
Point Of Sale ◽  
Storage Devices ◽  
Itemset Mining

With the advent of mass storage devices, databases have become larger and larger. Point-of-sale data, patient medical data, scientific data, and credit card transactions are just a few sources of the ever-increasing amounts of data. These large datasets provide a rich source of useful information. Knowledge Discovery in Databases (KDD) is a paradigm for the analysis of these large datasets. KDD uses various methods from such diverse fields as machine learning, artificial intelligence, pattern recognition, database management and design, statistics, expert systems, and data visualization.

Mastering Web Mining and Information Retrieval in the Digital Age

2017 ◽  
pp. 1-28 ◽  
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Information Retrieval ◽  
Organizational Performance ◽  
User Interfaces ◽  
Web Mining ◽  
Digital Age ◽  
Mass Storage ◽  
Web Data ◽  
Time Saving ◽  
Storage Devices ◽  
Collaborative Information Retrieval

This chapter aims to master web mining and Information Retrieval (IR) in the digital age, thus describing the overviews of web mining and web usage mining; the significance of web mining in the digital age; the overview of IR; the concept of Collaborative Information Retrieval (CIR); the evaluation of IR systems; and the significance of IR in the digital age. Web mining can contribute to the increase in profits by selling more products and by minimizing costs. Web mining is the application of data mining techniques to discover the interesting patterns from web data in order to better serve the needs of web-based multifaceted applications. Mining web data can improve the personalization, create the selling opportunities, and lead to more profitable relationships with customers in global business. Web mining techniques can be applied with the effective analysis of the clearly understood business needs and requirements. Web mining builds the detailed customer profiles based on the transactional data. Web mining is used to create the personalized search engines which can recognize the individuals' search queries by analyzing and profiling the web user's search behavior. IR is the process of obtaining relevant information from a collection of informational resources. IR has considerably changed with the expansion of the Internet and the advent of modern and inexpensive graphical user interfaces and mass storage devices. The effective IR system, including an active indexing system, not only decreases the chances that information will be misfiled but also expedites the retrieval of information. Regarding IR utilization, the resulting time-saving benefit increases office efficiency and productivity while decreasing stress and anxiety. Most IR systems provide the advanced searching capabilities that allow users to create the sophisticated queries. The chapter argues that applying web mining and IR has the potential to enhance organizational performance and reach strategic goals in the digital age.

Compromising Electromagnetic Emanations of USB Mass Storage Devices

2020 ◽  
Author(s):  
Alexandru Boitan ◽  
Simona Halunga ◽  
Valerică Bîndar ◽  
Octavian Fratu
Keyword(s):  
Mass Storage ◽  
Storage Devices

Automatically Correcting for Specimen Displacement Error During XRD Search/Match Identification

1981 ◽  
Vol 25 ◽  
pp. 231-236 ◽  
Author(s):  
Walter N. Schreiner ◽  
Ronald Jenkins
Keyword(s):  
Systematic Errors ◽  
Computer Search ◽  
Mass Storage ◽  
Storage Devices ◽  
The Past ◽  
Correct Analysis ◽  
New Ideas ◽  
On Line ◽  
Diffraction Patterns ◽  
New Algorithms

Over the past several years there has been considerable interest in computer search/match programs for qualitative analysis of powder diffraction patterns. This interest has been stimulated by the availability of modern minicomputers supported by relatively inexpensive mass storage devices capable of containing the entire JCPDS (l) data base on line. As the traditional search/match algorithms have been reviewed for possible implementation on the slower speed and restricted memory minicomputers being supplied with today's automated diffractometers, new ideas have emerged for such algorithms. One very extensive set of new algorithms has been developed by our group and these are contained in the SANDMAN search/match/identify program which was described at this conference last year (2). Experience has shown those algorithms to be extremely effective, particularly in handling eases where the presence of systematic errors in the data has precluded the correct analysis by other computerised search/match systems.

Present and future developments of SPM systems as mass storage devices

1999 ◽  
Vol 68 (2) ◽  
pp. 131-135 ◽  
Author(s):  
A. Born ◽  
R. Wiesendanger
Keyword(s):  
Mass Storage ◽  
Storage Devices ◽  
Future Developments
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